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  <h3>search.py (<a href="../search.py">original</a>)</h3>
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<span style="color: green; font-style: italic"># search.py
# ---------
# Licensing Information: Please do not distribute or publish solutions to this
# project. You are free to use and extend these projects for educational
# purposes. The Pacman AI projects were developed at UC Berkeley, primarily by
# John DeNero (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).
# For more info, see http://inst.eecs.berkeley.edu/~cs188/sp09/pacman.html

</span><span style="color: darkred">"""
In search.py, you will implement generic search algorithms which are called
by Pacman agents (in searchAgents.py).
"""

</span><span style="color: blue; font-weight: bold">import </span>util

<span style="color: blue; font-weight: bold">class </span>SearchProblem<span style="font-weight: bold">:
    </span><span style="color: darkred">"""
    This class outlines the structure of a search problem, but doesn't implement
    any of the methods (in object-oriented terminology: an abstract class).

    You do not need to change anything in this class, ever.
    """

    </span><span style="color: blue; font-weight: bold">def </span>getStartState<span style="font-weight: bold">(</span><span style="color: blue">self</span><span style="font-weight: bold">):
        </span><span style="color: darkred">"""
        Returns the start state for the search problem
        """
        </span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()

    </span><span style="color: blue; font-weight: bold">def </span>isGoalState<span style="font-weight: bold">(</span><span style="color: blue">self</span><span style="font-weight: bold">, </span>state<span style="font-weight: bold">):
        </span><span style="color: darkred">"""
          state: Search state

        Returns True if and only if the state is a valid goal state
        """
        </span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()

    </span><span style="color: blue; font-weight: bold">def </span>getSuccessors<span style="font-weight: bold">(</span><span style="color: blue">self</span><span style="font-weight: bold">, </span>state<span style="font-weight: bold">):
        </span><span style="color: darkred">"""
          state: Search state

        For a given state, this should return a list of triples,
        (successor, action, stepCost), where 'successor' is a
        successor to the current state, 'action' is the action
        required to get there, and 'stepCost' is the incremental
        cost of expanding to that successor
        """
        </span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()

    </span><span style="color: blue; font-weight: bold">def </span>getCostOfActions<span style="font-weight: bold">(</span><span style="color: blue">self</span><span style="font-weight: bold">, </span>actions<span style="font-weight: bold">):
        </span><span style="color: darkred">"""
         actions: A list of actions to take

        This method returns the total cost of a particular sequence of actions.  The sequence must
        be composed of legal moves
        """
        </span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()


</span><span style="color: blue; font-weight: bold">def </span>tinyMazeSearch<span style="font-weight: bold">(</span>problem<span style="font-weight: bold">):
    </span><span style="color: darkred">"""
    Returns a sequence of moves that solves tinyMaze.  For any other
    maze, the sequence of moves will be incorrect, so only use this for tinyMaze
    """
    </span><span style="color: blue; font-weight: bold">from </span>game <span style="color: blue; font-weight: bold">import </span>Directions
    s <span style="font-weight: bold">= </span>Directions<span style="font-weight: bold">.</span>SOUTH
    w <span style="font-weight: bold">= </span>Directions<span style="font-weight: bold">.</span>WEST
    <span style="color: blue; font-weight: bold">return  </span><span style="font-weight: bold">[</span>s<span style="font-weight: bold">,</span>s<span style="font-weight: bold">,</span>w<span style="font-weight: bold">,</span>s<span style="font-weight: bold">,</span>w<span style="font-weight: bold">,</span>w<span style="font-weight: bold">,</span>s<span style="font-weight: bold">,</span>w<span style="font-weight: bold">]

</span><span style="color: blue; font-weight: bold">def </span>depthFirstSearch<span style="font-weight: bold">(</span>problem<span style="font-weight: bold">):
    </span><span style="color: darkred">"""
    Search the deepest nodes in the search tree first
    [2nd Edition: p 75, 3rd Edition: p 87]

    Your search algorithm needs to return a list of actions that reaches
    the goal.  Make sure to implement a graph search algorithm
    [2nd Edition: Fig. 3.18, 3rd Edition: Fig 3.7].

    To get started, you might want to try some of these simple commands to
    understand the search problem that is being passed in:

    print "Start:", problem.getStartState()
    print "Is the start a goal?", problem.isGoalState(problem.getStartState())
    print "Start's successors:", problem.getSuccessors(problem.getStartState())
    """
    </span><span style="color: red">"*** YOUR CODE HERE ***"
    </span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()

</span><span style="color: blue; font-weight: bold">def </span>breadthFirstSearch<span style="font-weight: bold">(</span>problem<span style="font-weight: bold">):
    </span><span style="color: darkred">"""
    Search the shallowest nodes in the search tree first.
    [2nd Edition: p 73, 3rd Edition: p 82]
    """
    </span><span style="color: red">"*** YOUR CODE HERE ***"
    </span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()

</span><span style="color: blue; font-weight: bold">def </span>uniformCostSearch<span style="font-weight: bold">(</span>problem<span style="font-weight: bold">):
    </span><span style="color: red">"Search the node of least total cost first. "
    "*** YOUR CODE HERE ***"
    </span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()

</span><span style="color: blue; font-weight: bold">def </span>nullHeuristic<span style="font-weight: bold">(</span>state<span style="font-weight: bold">, </span>problem<span style="font-weight: bold">=</span><span style="color: blue">None</span><span style="font-weight: bold">):
    </span><span style="color: darkred">"""
    A heuristic function estimates the cost from the current state to the nearest
    goal in the provided SearchProblem.  This heuristic is trivial.
    """
    </span><span style="color: blue; font-weight: bold">return </span><span style="color: red">0

</span><span style="color: blue; font-weight: bold">def </span>aStarSearch<span style="font-weight: bold">(</span>problem<span style="font-weight: bold">, </span>heuristic<span style="font-weight: bold">=</span>nullHeuristic<span style="font-weight: bold">):
    </span><span style="color: red">"Search the node that has the lowest combined cost and heuristic first."
    "*** YOUR CODE HERE ***"
    </span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()


</span><span style="color: green; font-style: italic"># Abbreviations
</span>bfs <span style="font-weight: bold">= </span>breadthFirstSearch
dfs <span style="font-weight: bold">= </span>depthFirstSearch
astar <span style="font-weight: bold">= </span>aStarSearch
ucs <span style="font-weight: bold">= </span>uniformCostSearch

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